{"id":"W2999794418","doi":"10.4271/2019-36-0285","title":"Step-by-step correlation between calculated and measured data in order to reduce errors by vehicle simulation tools","year":2020,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Real-time simulation and control systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Chrysler (Canada)","funders":"","keywords":"Correlation; Computer science; Order (exchange); Data correlation; Mathematics; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005810285,0.0005878411,0.0008798962,0.0001369806,0.0001541708,0.0001783283,0.0006370094,0.0007373194,0.0001146041],"category_scores_gemma":[0.001537473,0.0005771994,0.00009055631,0.001499998,0.0001608164,0.0009203904,0.0002661781,0.000837857,0.00009272531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002279853,"about_ca_system_score_gemma":0.00004711895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009957838,"about_ca_topic_score_gemma":0.006031675,"domain_scores_codex":[0.9961013,0.0001990289,0.001208602,0.001071509,0.000792244,0.0006272937],"domain_scores_gemma":[0.9976228,0.0005066498,0.0001387108,0.001069786,0.0001425514,0.0005194879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002428292,0.00006177846,0.0009934746,0.00005285129,0.0000549515,0.000007730891,0.00004436098,0.02405566,0.9513036,0.000112219,0.01063209,0.01243846],"study_design_scores_gemma":[0.00188263,0.0004491388,0.9239936,0.0001723169,0.00008115012,0.000004821954,0.00008046461,0.002932359,0.00008161674,0.00002356594,0.06947085,0.0008274536],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9655653,0.00114184,0.001040653,0.00925226,0.000319742,0.004609933,0.0008082059,0.005692927,0.01156914],"genre_scores_gemma":[0.9971567,0.00004432193,0.000921273,0.0007941803,0.0001070806,0.0001006606,0.00065867,0.0001298074,0.00008725287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.951222,"threshold_uncertainty_score":0.9996679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02883421915738734,"score_gpt":0.2673400079274645,"score_spread":0.2385057887700771,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}